Non-small cell lung cancer (NSCLC) is the leading cause of cancer death in the United States. Current treatment options are limited and NSCLC patients have one of the lowest 5-year survival rates at 15%. This underscores the need for more effective NSCLC therapeutics. Of great interest are the new cancer immunotherapies - in particular blockade of the programmed death 1 (PD-1) signaling pathway - in treating NSCLC. PD-1 is a critical immune activation checkpoint, which when either blocked, or genetically ablated, leads to autoimmunity. It is known that PD-1 expression on T cells correlates with function inactivity, or an exhausted state, which is frequently observed in cancer. In addition, tumor cell expression of the ligand of PD-1, PD-L1, is associated with suppression of T cell driven immune responses against the tumor. PD-1 blocking therapies, such as antibodies against PD-1 (anti-PD-1), have shown a roughly 18% objective response rate in NSCLC trials, and patient tumor cell expression of PD-L1 was correlated with treatment response rate. The one out of five response rate for anti-PD-1 demonstrates a need for fine analysis to identify responders and non-responders. Current approaches for prognostic biomarker identification rely on histology of primary patient samples. These analyses have a very limited set of parameters to investigate the tissue samples collected are extremely valuable, thus exhaustive biomarker identification is not feasible with those methods. Mouse models of NSCLC have been informative in dissecting mechanistic information such as cancer driver mutations that underlie disease. These models are also useful from a therapy perspective, especially in the case of anti-PD-1 response as epidermal growth factor receptor (EGFR) mutation driven NSCLC is sensitive to anti-PD-1, yet Kras mutation driven NSCLC remains refractory to treatment. In this proposal, I intend to investigate key differences between EGFR and Kras driven NSCLC at both the tumor cell and microenvironment level that are correlated with a positive response to anti-PD-1. These correlations made in mice can identify novel biomarkers of anti-PD-1 response, which can then be tested in humans using standard histology approaches. This enables a more exhaustive biomarker analysis compared to what is available at present. Additionally, these studies can guide future clinical investigations into stratifying NSCLC patients by cancer driver mutations to associated anti-PD-1 response rates. My preliminary studies also identified PD-1 expression on Kras driven tumor cells, and that anti-PD-1 treatment of Kras driven tumors led to increased tumor burdens. This suggests the possibility of a tumor cell intrinsic role of PD-1 signaling that may be relevant to the biology of anti-PD-1 therapeutic response.